{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#  mplfinance: customization and styles\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This allows multiple outputs from a single jupyter notebook cell:\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read in daily data for the S&P 500 from November of 2019 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 5)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-11-01</th>\n",
       "      <td>3050.72</td>\n",
       "      <td>3066.95</td>\n",
       "      <td>3050.72</td>\n",
       "      <td>3066.91</td>\n",
       "      <td>510301237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-04</th>\n",
       "      <td>3078.96</td>\n",
       "      <td>3085.20</td>\n",
       "      <td>3074.87</td>\n",
       "      <td>3078.27</td>\n",
       "      <td>524848878</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close     Volume\n",
       "Date                                                     \n",
       "2019-11-01  3050.72  3066.95  3050.72  3066.91  510301237\n",
       "2019-11-04  3078.96  3085.20  3074.87  3078.27  524848878"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-11-27</th>\n",
       "      <td>3145.49</td>\n",
       "      <td>3154.26</td>\n",
       "      <td>3143.41</td>\n",
       "      <td>3153.63</td>\n",
       "      <td>421853938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-29</th>\n",
       "      <td>3147.18</td>\n",
       "      <td>3150.30</td>\n",
       "      <td>3139.34</td>\n",
       "      <td>3140.98</td>\n",
       "      <td>286602291</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close     Volume\n",
       "Date                                                     \n",
       "2019-11-27  3145.49  3154.26  3143.41  3153.63  421853938\n",
       "2019-11-29  3147.18  3150.30  3139.34  3140.98  286602291"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily = pd.read_csv('../data/SP500_NOV2019_Hist.csv',index_col=0,parse_dates=True)\n",
    "daily.index.name = 'Date'\n",
    "daily.shape\n",
    "daily.head(2)\n",
    "daily.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "v = daily['Volume'] / 10000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily['Volume'] = v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mplfinance as mpf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 518.4x372.6 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 518.4x372.6 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpf.plot(daily,type='candle',volume=True,figscale=0.9)\n",
    "mpf.plot(daily,type='candle',volume=True,figscale=0.9,show_nontrading=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-11-01</th>\n",
       "      <td>3050.72</td>\n",
       "      <td>3066.95</td>\n",
       "      <td>3050.72</td>\n",
       "      <td>3066.91</td>\n",
       "      <td>51030.1237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-04</th>\n",
       "      <td>3078.96</td>\n",
       "      <td>3085.20</td>\n",
       "      <td>3074.87</td>\n",
       "      <td>3078.27</td>\n",
       "      <td>52484.8878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-05</th>\n",
       "      <td>3080.80</td>\n",
       "      <td>3083.95</td>\n",
       "      <td>3072.15</td>\n",
       "      <td>3074.62</td>\n",
       "      <td>58563.4570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-06</th>\n",
       "      <td>3075.10</td>\n",
       "      <td>3078.34</td>\n",
       "      <td>3065.89</td>\n",
       "      <td>3076.78</td>\n",
       "      <td>54428.8522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-07</th>\n",
       "      <td>3087.02</td>\n",
       "      <td>3097.77</td>\n",
       "      <td>3080.23</td>\n",
       "      <td>3085.18</td>\n",
       "      <td>56611.7910</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close      Volume\n",
       "Date                                                      \n",
       "2019-11-01  3050.72  3066.95  3050.72  3066.91  51030.1237\n",
       "2019-11-04  3078.96  3085.20  3074.87  3078.27  52484.8878\n",
       "2019-11-05  3080.80  3083.95  3072.15  3074.62  58563.4570\n",
       "2019-11-06  3075.10  3078.34  3065.89  3076.78  54428.8522\n",
       "2019-11-07  3087.02  3097.77  3080.23  3085.18  56611.7910"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily.head()\n",
    "len(daily)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily.loc['2019-11-12','Volume'] = 0.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 518.4x372.6 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpf.plot(daily,type='candle',volume=True,figscale=0.9)\n",
    "#mpf.plot(daily,type='candle',volume=True,figscale=0.9,show_nontrading=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "apd = mpf.make_addplot(daily['Close'],panel='lower',secondary_y=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 518.4x372.6 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpf.plot(daily,type='candle',volume=True,figscale=0.9,addplot=apd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily.loc['2019-11-12','Low'] = 0.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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s2bPZsWOHo5sXQgghWo3Di+q6devo3Lkz9957r3XZI488QpcuXXj11Vcd3bwQQgjRahxeVHNycpgxYwY33nijddnw4cOZNm1ao5uJCyGEEO7O4UU1MDCQL7/8EqPRaF1WUVHB9u3b0el0jm5eCCGEaDUOH/07ZcoUXnnlFUaMGMF1112HxWIhPz+f+vp6HnroIUc3L4QQQrQahxfVBx98kIqKCjZv3kxubm5Dox4eTJs2jd/97neObl4IIYRoNQ4vqmq1msWLF/PII4+Ql5eH2WwmIiLimqYorKur489//jNvvPEGX3zxBZ07d2b37t3MnTuXsLAw6/OmT5/O9OnTMZlMJCYmsnv3bjQaDVOmTCEhIQGA/Px8li1bRn5+Pr6+vixZsoQRI0bYfb+FEEK0Pw4pqt999x3dunUjODiY77777pL1hw4dsv48dOjQq77eggUL6NevX6NlFRUVDBkyhI0bN17y/KSkJMrKykhLS6OsrIxJkyYxaNAg+vfvz/Lly4mNjWXWrFkcOHCA+fPns337dry9vW3YUyGEEOJ/HFJUExISeP7555k0aRIzZsywTqJ/MZVK1ajAXsnDDz/MwIEDWb9+vXVZRUUF/v7+l31+eno6jz76KGq1Gr1ej8FgID09na5du5KZmcnatWsBGDBgAGFhYWRmZhIbG2vDngohhBD/45CiOmTIEIKDg4HmHYlezcCBAy9ZVlFRwbFjx5g2bRpFRUUMHjyYp556Cn9/f3Jzc4mMjLQ+NzIyki+++IK8vDzrvVwvXJebmytFVQghRIs5pKi++eabl/3ZniIiIoiNjWXu3LlotVqWLFnCCy+8wB//+Edqamrw8vKyPtfb2xuj0XjJcgAvLy+qq6sbLVOpVISHOO9yH62HxqntuzNn586d3zdn585dSd5s15LcqdWX7wF1NocPVBo0aBCLFi3i/vvvt+vrjh07lrFjx1ofP/jggzzwwAMA+Pj4UFtba11nNBrx9fW9ZDlATU1NoyNXAEVROFVQadd4r0V4iM6p7bszZ+fOnd83Z+fOXUnebNeS3FksiksWVodP/nDTTTeRmZmJoih2fd0zZ85QVFRkfawoCh4eDX8jdO/evdFsTVlZWURHRxMVFUVJSQnl5eWXrBNCCCFayuFHqkFBQaSnpzN27Fh69uyJj4+PdZ1KpbIOGrpW77zzDgcPHmTNmjVoNBrefPNNbr75ZgDi4uJITU0lNjaWoqIiMjIyeP3119HpdIwePZqUlBTmz5/Pzp07KSkpYdiwYfbYVSGEEO2cw4vqW2+9Zf353LlzjdZdaVTwhQoLC5k+fbr18YwZM9BoNGzcuJHTp08zfvx41Go1AwcOtN70PCEhgZycHAwGAxqNhoULFxITEwNAYmIiS5YsYevWreh0OtasWYNWq7XHrgohhGjnVIq9+2UvsnXr1iaL58SJEx3Z/DULDAzEYlHYeyjPaTHIORrbOSt30RF6ALJOlLR62/YinzvbSN5s15LcDeoThVqtorS01M5RtYzDj1QnTJhAfX39JYOBhBBCiLbGYQOVqqqqeOyxx7jxxhsZMmQIs2bNIj8/31HNCSGEEE7nsKK6fv160tLSMJvNqNVqdu3axaJFixzVnBBCCOF0DiuqH330ETfccAO7du1i3759JCQksHfvXrKzsx3VpBBCCOFUDiuqhYWF3HnnnXTo0AEPDw9mzJiBoigUFBQ4qkkhhBDCqRxWVC0WS6M7v5y/PtVsNjuqSSGEEMKpHDr6t7a2lsrKhuHS5/+vqamx/gyg08mcmUIIIdoGhxbV559/nueff976WKVS8bvf/a7R4+bc+k0IIYRwBw4tqlebV8LB804IIYQQrcphRfXIkSOOemkhhBDCJTn8LjVCCCFEeyFFVQghhLATKapCCCGEnUhRFUIIIexEiqoQQghhJ1JUhRBCCDuRoiqEEELYiVsU1bq6Ol566SV69erFmTNnrMuTkpKIi4tj3LhxLFu2DJPJBIDJZGLZsmWMGzeO+Ph4Nm3aZN0mPz+f2bNnM27cOCZOnMiuXbtafX+EEEK0TW5RVBcsWNBocn6Affv2sWnTJrZs2UJaWhpFRUVs3rwZaCi2ZWVlpKWlkZKSQlJSEj/88AMAy5cvJzY2loyMDBITE3n88cepqalp9X0SQgjR9rhFUX344Yd55JFHGi1LT08nPj6egIAA1Go1U6dOJS0tzbpu8uTJqNVq9Ho9BoOB9PR0KioqyMzMZPLkyQAMGDCAsLAwMjMzW32fhBBCtD1uUVQHDhx4ybJjx44RGRlpfRwREUFOTg4Aubm5jdZFRkaSk5NDXl4eer0eX1/fRutyc3MdGL0QQoj2wqET6juS0WhEq9VaH3t7e2M0GoGG28t5eXldsu7i5QBeXl5UV1c3WqZSqQgPcd4t6bQeGqe2786cnTt3ft+cnTt3JXmzXUtyp1ar7ByNfbhtUfXx8bEOTIKGInv+CNTHx4fa2tpL1l28HBoK8IVHrtBw95xTBZU4S3iIzqntuzNn586d3zdn585dSd5s15LcWSyKSxZWt+j+vZzu3btbu3sBsrKyiI6ObnJdVFQUJSUllJeXX3Y7IYQQoiXctqjGxcVZR/3W19eTmprK+PHjretSU1Mxm80UFBSQkZFBfHw8Op2O0aNHk5KSAsDOnTspKSlh2LBhztwVIYQQbYTLd/8WFhYyffp06+MZM2ag0WhITk5m7ty5TJs2DUVRGDVqFFOnTgUgISGBnJwcDAYDGo2GhQsXEhMTA0BiYiJLlixh69at6HQ61qxZ0+jcrBBCCGErlaIoirODcCWBgYFYLAp7D+U5LQY5R2M7Z+UuOkIPQNaJklZv217kc2cbyZvtWpK7QX2iUKtVlJaW2jmqlnHb7l8hhBDC1UhRFUIIIexEiqoQQghhJ1JUhRBCCDuRoiqEEELYiRRVIYQQwk6kqAohhBB2IkVVCCGEsBMpqkIIIYSdSFEVQggh7ESKqhBCCGEnUlSFEEIIO5GiKoQQQtiJFFUhhBDCTqSoCiGEEHYiRVUIIYSwEymqQgghhJ14ODuAlujbty8RERHWxwMGDODll18mKSmJLVu2YLFYGDJkCCtWrECr1WIymUhMTGT37t1oNBqmTJlCQkKCE/dACCFEW+K2RbWqqgqVSkV6enqj5fv27WPTpk28//776HQ6FixYwObNm5kzZw5JSUmUlZWRlpZGWVkZkyZNYtCgQfTv399JeyGEEKItcdvu38rKSgICAi5Znp6eTnx8PAEBAajVaqZOnUpaWpp13eTJk1Gr1ej1egwGwyVFWQghhLCV2xbV8vJyzGYz8+bNw2AwMHfuXLKzszl27BiRkZHW50VERJCTkwNAbm5uo3WRkZHWdUIIIURLuW33r7e3NwaDgdmzZxMZGcmmTZtYsGABnTt3RqvVNnqe0WgEoKamBi8vr8uuu5BKpSI8ROf4nbgCrYfGqe27M2fnzp3fN2fnzl1J3mzXktyp1So7R2MfbltUIyIiSExMtD6eOXMma9euJTw8HJPJZF1uNBrx9fUFwMfHh9ra2suuu5CiKJwqqHRg9E0LD9E5tX135uzcufP75uzcuSvJm+1akjuLRXHJwurW3b8nTpywPlapVFgsFnx8fBp16WZlZREdHQ1A9+7dr7hOCCGEaCm3Lao//fQTM2bMoLCwEIB//etfdO7cmQcffJC0tDSKioqor68nNTWV8ePHAxAXF0dqaipms5mCggIyMjKIj4935m4IIYRoQ9y2+3fo0KHMmjWL+++/H5VKRUhICOvWraNHjx7MnTuXadOmoSgKo0aNYurUqQAkJCSQk5ODwWBAo9GwcOFCYmJinLwnQggh2gqVoiiKs4NwJYGBgVgsCnsP5TktBjlHYztn5S46Qg9A1omSVm/bXuRzZxvJm+1akrtBfaJQq1WUlpbaOaqWcdvuXyGEEMLVSFEVQggh7ESKqhBCCGEnUlSFEEIIO5GiKoQQQtiJFFUhhBDCTqSoCiGEEHYiRVUIIYSwEymqQgghhJ1IURVCCCHsRIqqEEIIYSdSVIUQQgg7kaIqhBBC2IkUVSGEEMJOpKgKIYQQdiJFVQghhLATKapCCCGEnbS7orpz504mTpzIuHHjmD17NmfOnHF2SEIIIdqIdlVUq6ur+f3vf8/zzz9PRkYGY8aM4ZlnnnF2WEIIIdqIdlVUd+3aRUREBH379gVgypQpfP3111RWVjo5MiGEEG1Buyqqx44dIyIiwvrYz8+PwMBAjh8/7sSohBBCtBUezg6gNRmNRry8vBot8/Lyorq6utEylUpFeIiuNUNrROuhcWr77sxZuTPW1rV6m/YmnzvbSN5s15LcqdUqO0djH+2qqPr6+lJbW9toWU1NDX5+fo2WKYrCqQLndQmHh+ic2r47k9zZTnJnG8mb7VqSO4tFccnC2q66f7t3705ubq71cXFxMWVlZURFRTkxKiGEEG1Fuyqqw4cP58yZM+zevRuAN998k1tuuQVfX18nRyaEEKItaFfdv97e3qxevZpnn30Wo9FIZGQkL774orPDEkII0Ua0q6IKDUerH374obPDEEII0Qa1q+5fIYQQwpFUiqIozg7ClahUDaPJfH39rvJMR8YA8q7YRnJnO8mdbSRvtmtJ7qqrq4CGqzVcSbvr/m0ulROHaqvkt9RmkjvbSe5sI3mzXVvMnRTVi3To0AGLRWHvoTynxSDXvdlOcmc7yZ1tJG+2a0nuBvWJkutU6+rqeOmll+jVq1eju8MkJSURFxfHuHHjWLZsGSaTCQCTycSyZcsYN24c8fHxbNq0ybpNfn4+s2fPZty4cUycOJFdu3ZZ1zV1J5ortSWEEO2JoijsPVnKmfIaZ4diVxkZGdx9990YDAamTp3K0aNHASgqKmL27NncfvvtjZ6/fv16hg8fjsFgsP47cOAA0HSduZJWLaoLFizA29u70bJ9+/axadMmtmzZQlpaGkVFRWzevBloKIBlZWWkpaWRkpJCUlISP/zwAwDLly8nNjaWjIwMEhMTefzxx6mpqWnyTjRNtSWEEO3F2Ypaln58mEXv/8islO/Z/N0J6swWZ4fVYvn5+axYsYL169eTnp6OwWBg6dKllJaWcv/999OzZ89LtqmoqGDOnDmkp6db/w0YMAC4cp1pSqsW1YcffphHHnmk0bL09HTi4+MJCAhArVYzdepU0tLSrOsmT56MWq1Gr9djMBhIT0+noqKCzMxMJk+eDMCAAQMICwsjMzOzyTvRNNWWEEK0dRZF4YMfTjM39Xu+zSvB21NNnVnhH5nHefCf+ziQX+bsEFvEw8ODVatWER4eDsDIkSPJzc1FpVKxfv16br311ku2qaiowN/f/7LLr1RnmtKqRXXgwIGXLDt27BiRkZHWxxEREeTk5ACQm5vbaF1kZCQ5OTnk5eWh1+sbzYQUGRlJbm5uk3eiaaotIYRoy06UVPPY1oOs+SIHY52Fm3oE8eb0wfzfPX3pEujN8RIjj209yKodWZTXuOcNIkJCQhg9ejQA9fX1vPfee9x222106NCB7t27X3ab8vJyPv/8c379618THx/Phg0bUBSlyTrTFKcPVDIajWi1Wutjb29vjEYj0DDZ/YV3lTm/7uLl8L+7zSiKcsV1TbV1IblLjfuS3NlOcmcbV89bndnCP/57jHX/ycZUbyFYp2X5+N6M69sZgP7dOnJ7/zBe+yqX177KYduhs+zKK+EpQy8mDAizXmboCI66S01ycjLr168nMjKSV199tcnXGTx4MJ6enkyePJmioiJmzpxJ586d6dKlS7PuanYxpxdVHx+fRoOFjEaj9S8DHx+fRneVOb/u4uXQUIB9fX1RFOWKd6Jpqq0LyV1q3JfkznaSO9u0dt5uW/ffJtdvXzja+vPP5yr5vx1ZZJ1ruKbT0DuEeaO74e/tcUnMv+7XmSHhAbzy72z255ez+N0f+Oe3J3j05u5c18HH/juC4+5SM3PmTBISEvjkk0+YMmUK27Ztu2Q8z4XPPS80NJT77ruPf//73zz44INXrDNNcfqMSt27d2/UBZuVlUV0dHST66KioigpKaG8vPySdU3diaaptoQQoq0w1Vt4fWceC/61n6xzVXT29+Klu/qw+Lbr8fe+8qLUCEcAACAASURBVLFUpN6XVRP7sfjWaPy9PNhzopS5qftI2e0eA5mys7P55ptvgIYexwkTJlBVVdVkl21WVlaj4qkoCh4eHk3WmaY4vajGxcVZR+LW19eTmprK+PHjretSU1Mxm80UFBSQkZFBfHw8Op2O0aNHk5KSAjRcQlNSUsKwYcOavBNNU20JIURb8EN+OQ/+cx9v7TmJosDEAWG8PnUQQyL1zdpepVJh6BNK0vQbub1XJ0xmC2/sOs5DW/bxQ3751V/AiYqLi3niiSc4e/YsAHv27KGurq7ROJuLPfvssyQlJQFQVlbGe++9x80339xknWlKq01TWFhYyPTp04H/DUDSaDQkJyeTkZFBSkoKiqIwatQo/vCHP+Dh4UFdXR3PPPMM3377LRqNhlmzZjFlyhQAzpw5w5IlS8jPz0en07F8+XJuvPFGADIzM1m5cmWjO9F06tQJgE2bNl22rfMCAwNl8gc3JrmzneTONq7W/XtepN6HRbdG0zcsoEXtfX+ilFf+k82psoZLScb3DeW3I7s2ecTbXPaY/KG0tLTR8s2bN5OamorFYkGr1fL4449jNpt5+eWXqampobCwkC5duhAaGkpycjInTpzg6aefJj8/H7VazV133cW8efNQqVRN1pkrkbl/LyJF1b1J7mwnubONqxVVjVrF1BvDuX9oBFqNfTojTfUWUvac4J97TlFvUQj08eThm7pxy/XBLRrI5Iii6mxO7/4VQghhP3+dfAOzR0TZraACaD3UzB4exd+mDKRfWAClxjpWfnqUJz88REm1zEp3ISmqQgjRhvQIdtwdtrp29GX1r/vx+C8DmXafKOWjg2euvmE7ck2d4uXl5eTl5REREYFOp0Oj0Tj0GiYhhBBgMlvYfbyE//xc6OxQUKtUxPcJZWRXPf/5uZDY64OdHZJLaVZRNZlMrFixgo8//pj6+nr+/ve/4+/vT2JiIn/729+sg4CEEELYR73Zwvcny/j3z4X8N6eIKpPZ2SE1ovfVMvGG65wdhstpVvfvCy+8wAcffMCgQYOsy+rr6zly5Agvvviiw4ITQoj2xGxR+P5EKX/ekcW9//iOpz46xKdHCqgymekR7MfcEVHODlFcRbOOVLdt28bcuXOZOXMmY8aMARqmdpo7dy5bt251aIBCCNGWWRSFg6fL+c/PhXyRVUSp8X/z7kbqfbjl+mBuuT6YCH3DTD4bdznvygRxdc0qqiqV6rKz+EPDEasQQohrl3G4gDd25VFY9b8RtOEdvLn5+mBujg6mW5CvjFtxM80qqv369ePvf/+7dZaKTz/9lLS0ND744AOGDx/u0ACFEKIt+jq7iD9t/xkFCPX3shbS6zv5SSF1Y80qqosXL2bmzJnW6ZrefvttFEUhICCApUuXOjRAIYRoa46creCFz46iALOGRzJ9SBcppG1Es4pqTEwM27Zt4/333+fYsWN4eXnRrVs3DAYDQUFBjo5RCCHajNPlNSz7+DC19Rbi+oRIQW1jmn2dalBQEHPnznVkLEII0aZV1NSz9KNDlBrruDGiA4/G9pCC2sY0q6hmZ2fzxz/+kYMHD1JZeek8jQcPHrR7YEIIcSXXck9RV1FntvBM2hGOlxjp1tGXFYYYPOw4laBwDc0qqosWLeLw4cOOjkUIIdokRVFYtSOLfafK6Ojryco7+6DzavldXoTrada7mpuby9ixY3n66acJDQ1FrZa/roQQorne/O4En/10Dm8PNSsn9CHU38vZIQkHaVZR/dWvfoVer6dLly6OjkcIIdqUT48UkPztCdQqWDauFz1DdM4OSThQs4rqihUrmDFjBpMnT6ZHjx6NbuqtUql49tlnHRagEMK5zBaFytp6ymrqKK+pp8xYR9kv/5fX1FFmrKe23kwHH0/0vlo6+nqi9/Wko68W/S/LtB7ts3dr78lSVu3IAuDhm7ozqltHJ0ckHK1ZRXXp0qUcOXIEgAMHDjRaJ0VVCPdmrDPz2ZECqs0KJ4urKDPWW4tlWU0dFTX1KC1sw0+r+V+hveB//S+Ft1uQL50DvO2yP64ir7iaFduOUG9RmHRDGPcMCHN2SKIVNKuofvXVVwQHB3PfffcRGhoqQ8CFaCPqzRZWbDvCnhOlTT7P38uDAG8POvh40uGX/wO8Pa3LvDRqSmvqKKmuo6TaREl1HcW//F9irKPKZKbKZOZkac1lX1+tgjv7dWbmsEg6+Hg6YldbVXG1iaUfHaLKZGZ09448NLqbs0MSraRZRbVr165MmDCBBx54wNHxCCFaiaIorPsqlz0nSgn08WTWqK6oLRY6eHsS4ONBgHdDAQ3w9kSjtv0PaYuiUFFTT4nx0oJbXF1HUZWJvSdL+eCHM+w4Wsis4ZHc2a9zi9p0ppo6M3/4+DBnKmrpFaJj6e093XZfxLVr9jnVl156iU6dOtGrV69G51QBoqOjHRKcEMJxtu4/zUcHz+CpUfHc+N7cPiCMUwWXXofeUmqVquEI18eTrh19L/uc3KIqXv0ql70ny1j7ZQ4fHzzDw2O7MahLoN3jcSSzReGPnx3lp4JKOvt78fyE3nh7apwdlmhFzSqq06ZNA2D//v2XrFOpVBw6dMi+UQkhHGpnbjF//ToXgCW/up4+nS9/F6rW0i3Ijz/d3Zf/5haz4etccourWfT+j4zp3pF5Y7oR5ibnW//232N8nVOMn1bDyjv70NFX6+yQRCtrVlHt1KmTnEcVoo3ILqzi+U9/sk7mfsv1nZwdEtDwB/qY7kEMi9Tzzr58Uvac4OucYjLzSrh3YDjTBnfBR+u6R33vHzjNu/vz8VCrSIyPueJRuWjbmlVUv/zyS0fHIYRoBUVVJpZ9fIiaOgu/6tWJ6UNc79pzrYeaaUO6cHtMJzbuzOOzn86RuuckGUcK+O2oKH7V0zX+CLjQN7nFvPpVDgC/vyXa7bqthf00q6hmZWU1uV7Oqbq3puZRdcU5VIVtaurMLP/kMOcqTfQL8+fzn87x+U/nLvtcV3jfO+m8ePL2ntzZrzOvfpXLTwWVvPjZz3z4wxlnh9bIwfwyVmb8hEWBhKERjOsd4uyQhBM1q6hOmDDhit2/9jin2rdvXyIiIqyPBwwYwMsvv0xSUhJbtmzBYrEwZMgQVqxYgVarxWQykZiYyO7du9FoNEyZMoWEhAQA8vPzWbZsGfn5+fj6+rJkyRJGjBgBwM6dO3n55Zeprq7muuuu449//COdO3duUeyiZdxxYnR3ZFEUXvz8Z34qqCQswJvE+N5M2vits8Nqlr5hAay7dwCfHing9Z15HDpT4eyQgIZBSQfyy3jp85+pqbdwe69OJAyLuPqGok1rVlENCQlpVFTr6uooKSkhMDCQqKioFgVQVVWFSqUiPT290fJ9+/axadMm3n//fXQ6HQsWLGDz5s3MmTOHpKQkysrKSEtLo6ysjEmTJjFo0CD69+/P8uXLiY2NZdasWRw4cID58+ezfft2LBYLv//973n99dfp27cvGzdu5JlnnmHDhg0tir+9k6LoHt7YdZyvsosaBtBM6E2gm10LqlapMPQO5aYeQaTsPsmW7085JQ6zReHg6XL+k1XIV9lFlFTXAXBDeACP3xotY0+E7edUT58+zZIlS5g+fXqLAqisrCQgIOCS5enp6cTHx1vXTZ06lXXr1jFnzhzS09N59NFHUavV6PV6DAYD6enpdO3alczMTNauXQs0HPGGhYWRmZmJ2WwmIiKCvn37AjBlyhRWr15NZWUlOp3MxSnarvTDZ3lrz0nUKlgRF0OUGw+g8dN68OCorlctqnVmC552uq2a2aLw4wWFtPiXQgoQFuDNnTeEMT4mxG7tCfdm872HwsLCuPPOO/nTn/7EHXfcYXMA5eXlmM1m5s2bx7FjxwgPD2fp0qUcO3aMW2+91fq8iIgIcnIaBgLk5uYSGRlpXRcZGckXX3xBXl4eer0eX1/fRutyc3OxWCyNupj9/PwIDAzk+PHj9OnTx+b4XYGcExVXsv9UGav/nQ3A/4vtweAI+w2gceXP3V2vZdKnsz8DrgtgQHgAvUP9r+l60fOF9IusIr7MLryokHoRGx1MbHQw13fyo0uo/zVd3yu9O21bs4rq999/3+ixoiicOXOGjRs3UlJS0qIAvL29MRgMzJ49m8jISDZt2sSCBQvo3LkzWq220fOMRiMANTU1eHl5XbLu4uUAXl5eVFdXoyjKFdddTKVSEd6Kd5KIeTrjiuuOPDuuRa/d0v1wt+21HppWfe9c2bGiKhLTf6LeojBzZBTzbm3+gEJHv29Nfeah5Z97k9nCvlNl7DtVBt+Bp0ZFv+s6MLSrnqFd9QyK1F9yP1OLReH746Wk/3iGjENnOVdRa13XRe+DoW8ohn6d6RsW0Kib196fOWf/zrWmluRO7aKzVDV78ofLnStQFAWDwdCiACIiIkhMTLQ+njlzJmvXriU8PByTyWRdbjQarUegPj4+1NbWXrLu4uXQUIB9fX1RFOWy6/z8/C67X46YWcYWLY2jvW0fHqJzmffOmcpr6lj49gHKjHWM7Krn/kHh15QXd3vfL/bu3GH8kF/OgfwyDuSXk32uir0nStl7opTXvspFrYLrO+nof10AvUJ0HDpTwZfZRRRV/e87p7O/F7HXBxPbI4ieITrrd2D+uapGbdn7M+fs3LWmluTOYlEuW1gzMjJYv349tbW16PV6EhMT6dmzJ0VFRSxatIiTJ0/y2WefWZ9v68DXK2lWUR00aNAlRdXPz49BgwYxa9as5rzEFZWXl1NWVmbtmlWpVFgsFnx8fKzdvdBwWc/5S3e6d+9OTk4OXbt2bbQuKiqKkpISysvLredis7KymDRpEmazmY8++sj6esXFxZSVlbV4oJUQrqbObOGZtCOcKquhR7Afy+7o1e7mng308eSmHkHc1CMIgMraeg6eLudAfjkHTpVx+GwlPxU0/LvY5EHhxEYH0euCQircQ35+PitWrODdd98lPDyc5ORkli5dyuuvv879999PbGwsJ0+ebLSNLQNfvb2vPMNXs4rqW2+91bI9bcJPP/3E4sWLeeeddwgODuZf//oXnTt35sEHH+T//b//x29/+1s6dOhAamoq48ePByAuLo7U1FRiY2MpKioiIyOD119/HZ1Ox+jRo0lJSWH+/Pns3LmTkpIShg0bhsVi4cyZM+zevZshQ4bw5ptvcssttzQ6/yrcjyuf13MGRVF45T/Z7D9VTpCvJ8+P7+3SsxC1Fp2XByO6dmRE14b7mTb1uXlodNdWikrYm4eHB6tWrSI8PByAkSNHsmbNGlQqFevXr+fcuXPs2LGj0Ta2DHyNjY29cgxXWnHhUd3V3Hnnnc1+7sWGDh3KrFmzuP/++1GpVISEhLBu3Tp69OjB3LlzmTZtGoqiMGrUKKZOnQpAQkICOTk5GAwGNBoNCxcuJCYmBoDExESWLFnC1q1b0el0rFmzxnpudvXq1Tz77LMYjUYiIyN58cUXbY5biJZyxICVLXtPkX64AC8PNc+N702Iv9fVNxKijQgJCSEkpGHyjfr6et577z1uu+02OnToQIcOHTh37tLJTmwZ+GpTUV28eHGzuz5aUlQBZs2addlu5ISEBGvf9oU8PT1ZuXLlZV+rc+fOJCcnX3bd8OHD+fDDD1sUqxCu6uvsIl7/Jg+Ap27vSa9Q506SL4SzJCcns379eiIjI3n11VebfK4tA1+bcsWi2tQsSkII13K0oJIXPjuKAjwwMsp6LlE4hjufdmgPl/TMnDmThIQEPvnkE6ZMmcK2bduueB7UloGvTbliUf2///u/a9kHIUQrMJrMnC6v4UxFLcs/OXzZ57y+M4+pg11vonwhHC07O5uzZ88yatQoVCoVEyZM4LnnniM3N5fevXtfdhtbBr42pdmTP2RnZ7Nlyxays7PRaDTExMSQkJBAcHBwc19CCHENPjp4mjPltZwpr+H0L/+X1dQ7OywhXFZxcTFPPPEE7777LqGhoezZs4e6urpGE/9czJaBr01pVlHds2cPc+bMwWQyoSgK0DB14VtvvcU777wjl6UI0Qz1ZgtF1XUUVtZyrtJ01ee/8p+cS5Z5alR09vemc4AX3x0vdUSYQritoUOHMm/ePGbPno3FYkGr1bJ69Wq+/fZbXn75ZWpqaigsLMRgMBAaGkpycrLNA1+vpFlF9ZVXXkFRFB566CH69euHoijs37+f5ORkVq5cyWuvvdbybAhhZ2aLctXrM+11bsxsUThbUcO5ShPnfimahZUmzlXVUlhporCyluLqOpRmvyIYeocQFtBQQDsHeNPZ34uOflrUv4x1uNq5MSHao+nTp192TvoLp729kK0DX6+kWUX14MGDzJkzh0cffdS67Pbbb0dRFIdewyrElZwoMZJ2+GyTz5m08VuGRekZ2U3P0MtMS9cStfVmjpyt/GXWnnIOnSnHWGdpchsVEOSnpZNOSyc/L77KKWry+Ytvu95u8QohWkezvmUURcHT89JbRfn5+WGxNP1FIoS91Nab+TK7iLQfz7I/v/yqz6+orWf70XNsP3oOjVrFgOsCGNm1IyO66gkP9Lmmtitr6/nxdLm1iB4tqKTO0vi4s5NOS6i/F8F+WoJ1Xg3FU9fwuJPOi46+nnhccCcTOdIUou1pVlHt378/b7zxBh06dGDAgAHW7t+NGzfSr18/R8co2rmsc5VsO3SWz386R5XJDIC3h5qbrw8m/XDBFbdLuv9Gdh4rZlduMT+cLmfvyTL2nixj/de5ROp9rLPrXMkXWYUcOFXOD6fLySmsatR1qwJ6BPvRPyyA/tcF0C/Mn2CdTLQgRHvXrKK6dOlS7r333kv6nTUaDU8++aRDAhMCYP6WfRy9YALzmFAd8X1Cufn6YPy0Hk0W1Qi9DxH6cCYPCqe8po7v8krZeayYb/NKOF5i5HhJ0/fkfDb9J+vPHmoVvUIaJmBvKKIBdu1OFkK0DU1+K2zfvp3Y2Fh69+7Nhx9+yIYNG/jpp4YvmpiYGH77299aJ7kXwhGOnqtC56Xh9l4hxPUJpUfwpXcVao4Ab09u69WJ23p1ot5s4YfT5ezMLeHd/flX3GZwRCD9rwtgwHUBxITq8PKQOXSFcOeJL1pDk0X14YcfRq/XEx8fz913383LL7/cWnEJAcDS23sypkdHuxY0D42aQV0CGdQlsMmi+vLdfe3WphCifVA3tbJPnz6UlJSQkpLCfffdh8Fg4K9//SunTjXdbSZEc2QXVl31Obf16iRHiEIIt9HkkerWrVs5ffo0n332GZ999hnff/89f/nLX1izZg033ngj99xzDwaDAX9/mbhbNE+d2cJX2UV88MNpDp6ucHY4QghhV1cdaREWFma9W0xpaSnbt29nx44d7Ny5k++//57nn3+e/fv3t0aswo2drajlkx/P8MmPZyk11gHgp9VYR/MKIURbcE3DFwMDA5kwYQKBgYEEBATw8ccfYzJdfbo10X7tPl7KBz+cZtexYs5f1tktyJe7+4fxq56dmPDaLucGKIQQdtSsolpeXs6///1vPv/8c77++mtqampQFIX+/ftzzz33ODpG4caWfPgj0HBJys3RQdzVP4x+Yf5yW0EhRJvUZFFNTU3l888/59tvv8VsNqMoCtdddx133nkn99xzD926dWutOIWNHn57Pz2C/Oge7Ef3IF+6Bfnh791611d20mm5s19n4nqH0tGv6YmohRDC3TX57frss88CDdMR3nHHHdx9992MGDGiVQITV2e2KHzy45kmn3PkbCVHzlY2Whai0/5SZP3oHtz0DXfPVdZSVGX6ZYL4WgrP//zLRPFXk5Iw5KqT2gshRFvRZFEdPXo0d999N3fccccV75ouWp+iKHybV8KG/x7jeImxyeeuuqcfOUVVDf8KqzlWXE1BpYmCShO7jpVcta0pSbtbFKsUVCFEe9JkUd24cWNrxSGaKaewig3/PcaeEw330gwL8OZ0ec0Vnz+wSwcGdulgfWy2KOSXGckpqiansIqcomq+yS2+4vaBPp500mmtk8IH67S/3GmlYaL4Oal77bdzQgjh5mTyUjdRXGUiKfM4aYfPYlEaLkeZMTSCuweEEffXnc1+HY1aRYTelwi9L7HRwUDT0469O7fpu9wLIYT4HymqLq623sw7+/J5a89JjHUW1CqYOCCMGUMj6OBz6e34hBBCOI8UVRc3a/P3FPwyIGhkVz0Pju5KpL7pwUVCCCGcQ4qqiyuoNNE9yJf5Y7pxY0Sgs8MRQgjRBCmqLm7RrdHcERMio2iFEMINNHmXmrZo586dTJw4kXHjxjF79mzOnGn6Ok9ni+sTKgVVCCHcRLsqqtXV1fz+97/n+eefJyMjgzFjxvDMM884OywhhBBtRLsqqrt27SIiIoK+fRtuPj1lyhS+/vprKisrr7KlEEIIcXUqRVEUZwfRWt544w1+/PFHVq1aZV02ZswYXnvtNfr06QOARqPBYrHg7x/QanFVmuqvuE6nvfppb2du39S2zt6+NXLXEu6+7/K5sX/b7r79tf7OqNUqLBbbSlBFRTlqtRqz2bVuH9muBioZjUa8vLwaLfPy8qK6utr6WKvVYjKZULfiecwA75Zdb+rM7d05dnts78y23Xl7d469pdu7c+z22P5itn7XqtVqtFrXu0lHuyqqvr6+1NbWNlpWU1ODn5+f9bHR2PRcukIIIcSVtKtzqt27dyc3N9f6uLi4mLKyMqKiopwYlRBCiLaiXRXV4cOHc+bMGXbvbrjzyptvvsktt9yCr6/MUNRetKMhBMKFyOeu/WhXA5UAMjMzWblyJUajkcjISF588UU6derk7LCuiaIoqFRy7apoPdnZ2XTr1g21ul39HS7ENWt3RdWdnThxgoiICEAK67VKSUmhpKSEG264gd69exMcHOzskNzGY489RseOHVm+fLmzQ3E7SUlJFBcXM2TIEPr27UtQUJCzQxIOpnlGZj9wC4mJibz99tuEh4fTpUsXVCqVFNZmevLJJ/n555/x9PTkiy++wMvLi969e0v+mmH58uVUVlby0ksvOTsUt7NkyRKys7Px8vJix44deHp60rdvX/nctXHtavSvOysoKCAsLIx3330XRVEYMWKEFNZm+PTTTzlx4gQpKSlAw7XKH330ERMnTpS8XcULL7zA999/zyeffALA9u3bOXfuHMHBwVx//fUywK8J33zzDadOnWLz5s0AbNy4kc2bN3P33Xe75GUgwn7kBIkbKCkpoba2ljFjxhAYGMjbb7/Nrl27AKyFVVxeQEAAnTt3pri4GIBbbrmFqqoqVq5cSVJSEtnZ2U6O0DVVVFSgKApjxoyhsLCQlJQU/vKXv7B7927eeustXnzxRQ4fPuzsMF2WVqtFp9NRWFgIwNSpU9FqtRQXF8vvaxsn3b9uwMfHh6ioKGJjY9Hr9Rw/fpw9e/YQEBBAREQEKpWKioqKSya2EFBfX8+bb77JuXPn+Pnnn1m+fDl33HEHISEhHD16lJMnTzJ48GDUarUcuV7Ay8uL8PBw9u7dyxdffMGPP/7I2rVrmThxIn379uXEiRMUFBRw4403AkjufmGxWFCpVGg0GjQaDf369cPT0xOLxcJ7773H7bffTkBAACqViqqqKjlqbYOk+9dFrV69mrNnz3LdddcxfPhwhg8fDkC/fv1Qq9Vs3bqVd955h06dOpGXl8f+/fv53e9+h6en82YIchXncxcWFkZcXByvvvoq27Zt48CBA4wePZrHHnsMgK1bt/Lpp5/KF9sFdu7cyciRIwHo0aMH9957Lxs2bKBnz574+vpiNpuJjo6mS5cu7N69W0YDX+Cll17i9OnTBAcHc9ddd3HvvfcCDX/YlZSUUFdXZy2on3zyCVlZWSxYsEB+Z9sY+Y1wQU899RTZ2dmMHDkSs9nM0qVL+ec//2ld36dPH379618TFRXFY489xsqVK7nrrrvkl5PGubNYLMybN4/9+/czf/58brvtNgIC/jens4eHB4qiUFVV5cSIXce6deuYPXs2r732mnVZnz59WLRoEb/5zW/w8/NDo9EADd3qvr6+mEwmZ4XrUp566ilOnjyJwWBArVbz+uuvc/bsWaBhPnEPDw+0Wi0BAQF88MEHrFmzhgkTJsjvbBskR6ou5uzZsxQWFvL3v/8dAJPJRO/evVm8eDEWi4Vp06YBDV92GRkZVFVV8dprrxEdHe3MsF3C5XIXExPDE088gclkYvDgwSxfvtx6xLVjxw5Wr17daJrK9sxisTBz5kw+/vhj6urqePjhhwGIjIwEIC8vj88++4ySkhJ27NjBK6+8Ikf5wKlTp8jPzyc5ORmA8PBwnnvuOeuUpyqVig4dOhAaGsqzzz7Ld999x9q1a+nRo4czwxYOIkeqLkav11NRUWEdrarVajEYDPz5z39m/fr1fP755wB8//33ZGZm8te//lUK6i8ul7u4uDhWrVrFn//8Z4xGI3/729+orKykpqaGtWvX0qtXLydH7RosFgt5eXkMHjyYxYsXs23bNtavX9/oOaWlpRw/fhyLxcK6deskd7/w8fGhtraWb7/9FkVR6N+/P35+fuTl5QFgNpupr6+nqqrK+sdIz549nRy1cBQZqORiNBoNFRUVHDt2jKCgIEJCQoCGeYvVajX79+9n7NixWCwWJkyYIJc1XKCp3KlUKr766itmzJjBTTfdRGxsLB07dnRyxK5DpVIxcuRI+vTpQ1hYGOHh4WzatInS0lKGDRsGgJ+fHwaDgTFjxkjuLqBWq+nZsycxMTHWwYIfffQRffr0sf7ems1mBg4cyD333CNHqG2cHKm6oFtvvZXTp0/zwQcfcOTIEaDhS69Xr16cOnUKs9lMREQEoaGhTo7U9Vwpd7179yY/P/+X2/rJx/5ydDod0HCEf9NNN/HYY4+xbds2UlJS+PTTT5k3bx6VlZVySchFvLy8uOGGG9DpdFgsFiwWCxqNxvr7+e677/LAAw/QpUsXunfvJP4AdgAABUpJREFU7uRohaPJt4uT1dc3vuGvxWKxDkDKy8vj7bffZtu2bQCUlZWhKMolt69rr641d4Dk7hcX5w5o9MeGVqtl7NixPPfcc/zpT3/ixRdf5Omnn0an07X7y2cul7vzA7hUKhVqtRpPT0+CgoLYtm0bSUlJLF++XC55aydk7l8XYLFY+Oyzzxg3bhwWiwVo+ILLycnh/fffZ9euXXh7e1NQUMArr7xCTEyMkyN2HZI7212YuyvNzJWamkpycjKvvvqqnLu/wNVyt3TpUo4cOUJdXR2rVq2Sc6jtiSKcbv/+/UqvXr2UAwcOWJdZLBZFURSltrZWKSkpUQ4cOKAUFBQ4K0SXJbmz3eVyd6FTp04pCxcuVA4fPtzKkbm+K+Xu/Gfv3XffVe68804lKyvLGeEJJ5KBSk5wftaV80JDQ1EUhaNHjzJkyJBGs/toNBq8vb0JDQ2VSz+Q3LXEteQOGrqAb7nlFq677jpnhOtSmpu788/p2LEjd911l/WuUqL9kHOqTqBWq1EUhf/+97/WZQMGDODAgQNUVlaiUqmsXZmiMcmd7a41d15eXtbBS+3dteROURRCQ0NlIGE7JUeqrejCv3Y/+OADXn75ZQ4cOECvXr244YYbOHjwINu2bSMuLq7dDwa5mOTOdpI729mSO8lh+yYDlVqJ2WxGo9GgKApFRUUYjUb8/PxYuXIl9fX1BAYGMnHiRD7++GPuu+8+rr/+emeH7DIkd7aT3NlOcidsIdMUtoLz161ZLBYWLlxIeXk5/v7+DB06lFWrVnH06FFSU1NZvHgxxcXFBAUFyS/oLyR3tpPc2U5yJ2wl3b+tRKVS8cgjj9C1a1eWLl1KYGAgH374IXv37uU3v/kNN998M926/f/27t8ltTCO4/gnAjGi0ixzlSiCorWhEKQh7C8Qoa1JaDoNDfYvOAouNTSWQ0EQONUktDgoNDSbky6RcEieO3Sv3J9wec5zKu59vybBBnnj4Zv6PeekFYvFlMvllEgkPvolfxq0s0c7e7SDlQ/YOP5v1Gq10eNut2v29vZMp9Mxxryd7tFqtcz+/r45Pz8f/d1wOHz31/kZ0c4e7ezRDkGx/RuSbrerm5sbHR8fS3pbwY/H46rX63p5eVEkEtHi4qLS6fToFlGSuISeaBcE7ezRDi7wbghJMpmU53nyfX90kGYyGTUaDTUaDT0/PysajWp2dlb9fl/D4ZBrqn5FO3u0s0c7uMD2b4heX1/1+PioarWqRCKhUqmkSqWih4cHjY2NaWVlRbVaTdVqlTtX/IR29mhnj3YIikUlh8rlsprNpqanpzUYDBSPxzU3N6fl5WXd3d3p/v5enudpYWFBvu/L9315nsfBKdoFQTt7tINrfFJ15OnpSdlsVpJULBZ1fX2tTCYz2gzs9Xq6vLxULBaT53mS3tb2+T2GdkHQzh7tEAY+qToyNTWlnZ0dXV1daXt7W0dHR4pEIqrX62q32zo7O9Pk5KQuLi5kjNHGxoYkrr4i0S4I2tmjHcLAxR8cWlpa0snJiQqFgsbHx5XP55XNZmWM0e3trfr9vgaDgXZ3dyVxcH6PdvZoZ492cO79z+L59zWbTbO6umpOT09/ee7braHwe7SzRzt7tIMrfP0bglQqpc3NTR0eHmpmZkbr6+s/PM9/u39GO3u0s0c7uMJQDUkqldLW1pYODg40Pz+vtbU1SRycf4N29mhnj3Zwge3fkLVaLU1MTLCCb4F29mhnj3YIgqEKAIAjnHAFAIAjDFUAABxhqAIA4AhDFQAARxiqAAA4wlAFAMARhioAAI4wVAEAcOQLC7gFaAfZE4gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 518.4x372.6 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpf.plot(daily,type='candle',volume=True,figscale=0.9,addplot=apd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 1.e-2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.01\n"
     ]
    }
   ],
   "source": [
    "print(x)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
